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    <title>浏阳德塔软件开发有限公司 女娲计划</title>
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    <br/>第七章 类人DNA与神经元基于催化算子映射编码方式
    <br/>The Initons Catalytic Reflection Between Humanoid DNA and Nero
    Cell
    <br/>类人 DNA 与 神经元基于催化算子映射编码方式
    <br/>Yaoguang Luo, Rongwu Luo
    <br/>罗瑶光, 罗荣武
    <br/>Keywords
    <br/>VPCS, AOPM, IDUC, Nero, Artificial, Decoder, Medical, Paralling,
    Computing,
    <br/>Humanoid, ETL, Parser, Data Mining
    <br/>关键词
    <br/>VPCS 架构 AOPM 逻辑 IDUC 编码 神经元 人工 解码 医学 并行计算 类人仿生 ETL 数据挖掘
    爬取

    <br/>
    <br/>2. 3 Deta Business backend logic application, 德塔商业后端逻辑应用
    <br/>
    In the whole year of 2019, the VPCS back-end engine gradually
    formed some standardized functions and papers, which were applied to
    the front-end, back-end, cache, database and other subsystems of DETA.
    My evaluation of them is that they are lightweight and extensible. VPCS
    is gradually integrated into the works of Yangliaojing and Huaruiji. Of
    course, there are many shortcomings, the biggest one is that they do
    not repair themselves. Although I designed the sleeper and hall-keeper
    mechanisms, these mechanisms are only the corresponding business logic
    units that I complete through decision trees, not humanoid evolutionary
    thinking. At least, I don't think they are humanoid intelligence. To be
    precise, at present, they are only artificial intelligence, a kind of
    artificial intelligence logic corresponding to AOPM and VPCS, but not
    the humanoid evolutionary intelligence logic that I want. So, I started
    to explore humanoid computing again. About the application principal
    description of VPCS, the author designed a paper as below:
    <br/>
    2019 年 一整年, VPCS 后端引擎 逐渐形成一些规范化函数和论文, 应用在德塔 前端, 后端,
    缓存, 数据库, 等子系统中, 我对他们的评价是, 轻巧, 可扩展. VPCS 逐渐集成在 养疗经
    和 华瑞集作品中. 当然不足也很多, 最大的不足是没有做到自我修复, 虽然我设计了 sleeper
    和 hallkeeper 机制, 但是这些机制只是 我通过决策树 来 完成相应的业务逻辑单元, 不是
    类人的进化思维. 至少我觉得不是类人智慧, 确切的说目前只是人工智慧. 一种 AOPM VPCS
    对应的人工智能逻辑. 而不是我想要的类人进化智慧逻辑. 于是我又开始了类人计算探索. 关于
    VPCS 应用原理描述: 作者设计了一篇论文如下:
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